0f297cad4d
It introduces a pattern that swaps `linalg.generic + tensor.pack` to `tensor.pack + linalg.generic`. It requires all the iteration types being parallel; the indexing map of output operand is identiy. They can all be relaxed in the future. The user can decide whether the propagation should be applied or not by passing a control function. Reviewed By: mravishankar Differential Revision: https://reviews.llvm.org/D138882
50 lines
1.6 KiB
C++
50 lines
1.6 KiB
C++
//===- TestDataLayoutPropagation.cpp --------------------------------------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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#include "mlir/Dialect/Affine/IR/AffineOps.h"
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#include "mlir/Dialect/Linalg/Transforms/Transforms.h"
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#include "mlir/Pass/Pass.h"
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#include "mlir/Pass/PassManager.h"
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#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
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using namespace mlir;
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namespace {
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struct TestDataLayoutPropagationPass
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: public PassWrapper<TestDataLayoutPropagationPass, OperationPass<>> {
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MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(TestDataLayoutPropagationPass)
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void getDependentDialects(DialectRegistry ®istry) const override {
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registry
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.insert<AffineDialect, linalg::LinalgDialect, tensor::TensorDialect>();
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}
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StringRef getArgument() const final {
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return "test-linalg-data-layout-propagation";
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}
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StringRef getDescription() const final {
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return "Test data layout propagation";
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}
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void runOnOperation() override {
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MLIRContext *context = &getContext();
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RewritePatternSet patterns(context);
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linalg::populateDataLayoutPropagationPatterns(patterns);
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if (failed(
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applyPatternsAndFoldGreedily(getOperation(), std::move(patterns))))
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return signalPassFailure();
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}
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};
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} // namespace
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namespace mlir {
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namespace test {
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void registerTestDataLayoutPropagation() {
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PassRegistration<TestDataLayoutPropagationPass>();
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}
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} // namespace test
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} // namespace mlir
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